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SISA Certified Security Professional in Artificial Intelligence Sample Questions (Q45-Q50):

NEW QUESTION # 45
In assessing GenAI supply chain risks, what is a critical consideration?

A. Focusing only on internal development risks.
B. Ignoring open-source dependencies to reduce complexity.
C. Assuming all vendors comply with standards automatically.
D. Evaluating third-party components for embedded vulnerabilities.

Answer: D

Explanation:
GenAI supply chain risk assessment prioritizes scrutinizing third-party libraries, datasets, and models for vulnerabilities like backdoors or biases, using tools for dependency scanning. This holistic view prevents cascade failures, as seen in compromised pretrained models. Mitigation includes vendor audits and secure sourcing. Exact extract: "A critical consideration in GenAI supply chain risks is evaluating third-party components for vulnerabilities." (Reference: Cyber Security for AI by SISA Study Guide, Section on Supply Chain Risk Assessment, Page 250-253).

NEW QUESTION # 46
In ISO 42001, what is required for AI risk treatment?

A. Delegating all risk management to external auditors.
B. Ignoring risks below a certain threshold.
C. Identifying, analyzing, and evaluating AI-specific risks with treatment plans.
D. Focusing only on post-deployment risks.

Answer: C

Explanation:
ISO 42001 mandates a systematic risk treatment process, involving identification of AI risks (e.g., bias, security), analysis of impacts, evaluation against criteria, and development of treatment plans like mitigation or acceptance. This ensures proactive management throughout the AI lifecycle. Exact extract: "ISO 42001 requires identifying, analyzing, and evaluating AI risks with appropriate treatment plans." (Reference: Cyber Security for AI by SISA Study Guide, Section on Risk Treatment in ISO 42001, Page 270-273).

NEW QUESTION # 47
In the context of LLM plugin compromise, as demonstrated by the ChatGPT Plugin Privacy Leak case study, what is a key practice to secure API access and prevent unauthorized information leaks?

A. Restricting API access to a predefined list of IP addresses
B. Implementing stringent authentication and authorization mechanisms, along with regular security audits
C. Increasing the frequency of API endpoint updates.
D. Allowing open API access to facilitate ease of integration

Answer: B

Explanation:
The ChatGPT Plugin Privacy Leak highlighted vulnerabilities in plugin ecosystems, where weak API security led to data exposure. Implementing robust authentication (e.g., OAuth) and authorization (e.g., RBAC), coupled with regular audits, ensures only verified entities access APIs, preventing leaks. IP whitelisting is less comprehensive, and open access heightens risks. Audits detect misconfigurations, aligning with secure AI practices. Exact extract: "Stringent authentication, authorization, and regular audits are key to securing API access and preventing leaks in LLM plugins." (Reference: Cyber Security for AI by SISA Study Guide, Section on Plugin Security Case Studies, Page 170-173).

NEW QUESTION # 48
A company's chatbot, Tay, was poisoned by malicious interactions. What is the primary lesson learned from this case study?

A. Chatbots should have limited conversational abilities to prevent poisoning.
B. Continuous live training is essential for enhancing chatbot performance.
C. Encrypting user data can prevent such attacks
D. Open interaction with users without safeguards can lead to model poisoning and generation of inappropriate content.

Answer: D

Explanation:
The Tay incident, where Microsoft's chatbot was manipulated via toxic inputs to produce offensive content, underscores the dangers of unfiltered live learning, leading to rapid poisoning. Key lesson: Implement safeguards like content filters, rate limits, and moderated feedback loops to prevent adversarial exploitation.
This informs AI security by emphasizing input validation and ethical alignment in interactive systems. Exact extract: "Open interactions without safeguards can lead to model poisoning and inappropriate content, as seen in the Tay case." (Reference: Cyber Security for AI by SISA Study Guide, Section on Case Studies in AI Poisoning, Page 160-163).

NEW QUESTION # 49
What does the OCTAVE model emphasize in GenAI risk assessment?

A. Solely technical vulnerabilities in AI models.
B. Short-term tactical responses over strategic planning.
C. Exclusion of stakeholder input in assessments.
D. Operational Critical Threat, Asset, and Vulnerability Evaluation focused on organizational risks.

Answer: D

Explanation:
OCTAVE adapts to GenAI by emphasizing organizational risk perspectives, identifying critical assets like models and data, evaluating threats, and prioritizing mitigations through stakeholder collaboration. It fosters a strategic, enterprise-wide approach to AI risks, integrating business impacts. Exact extract: "OCTAVE emphasizes operational critical threat, asset, and vulnerability evaluation in GenAI risk assessment." (Reference: Cyber Security for AI by SISA Study Guide, Section on OCTAVE for AI, Page 255-258).

NEW QUESTION # 50
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